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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

CCSI Toolset 3.21 Release

CCSI Toolset 3.21 Release Highlights Parallelization support was added for Sequential Design of Experiments (SDOE) computations using Dask (preliminary). Input type dependent ordering capability was added to the SDOE module. With this implementation the user can specify the level of difficulty to change an input (Easy or Hard) and FOQUS will generate the appropriate ordered design depending on the input difficulty combination. Python version support was extended. FOQUS is now compatible with Python 3.8 through 3.12. Platforms used for automated testing were expanded to include macOS ARM (Apple Silicon). Updates to the FOQUS documentation to include information on how to set paths for SimSinter and TurbineLite. Turbine configuration section was added to Debugging Documentation.

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DOE OSTI2024

CCSI Toolset 3.22 Release

CCSI Toolset 3.22 Release Highlights The Sequential Design of Experiments user interface was updated to resolve an issue where the results would fail to plot in some cases (e.g., Non-Uniform Space Filling designs). The Machine Learning/Artificial Intelligence module was updated to support Keras 3 and to reflect changes made to dependencies’ syntax. A check was added to ensure PSUADE is installed and available at FOQUS startup. If PSUADE is not installed, a link to the FOQUS documentation is displayed and FOQUS is closed. The copyright year was updated to include 2024 in places where it had not previously been updated. Typographical errors were corrected to improve clarity in variable names and documentation. The FOQUS documentation was updated to reflect the fact that ALAMO can have two executables and indicates the correct executable to add to the Settings path. SimSinter was updated to version 3.1.0. This version removed gPROMS support and included security updates.

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DOE OSTI2024

CCSI Toolset 3.23 Release

CCSI Toolset 3.23 Release Highlights The user interface was updated to allow timeouts in Aspen Custom Modeler and AspenPlus. The installation was updated to use 64-bit versions of TurbineLite and SimSinter by default. The documentation was improved for clarity.

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DOE OSTI2025

CCSI Toolset 3.24 Release

CCSI Toolset 3.24 Release Highlights Support for Python 3.8 was removed. Extraneous and wildcard imports were removed.

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DOE OSTI2025

CCSI Toolset 3.25 Release

CCSI Toolset 3.25 Release Highlights The copyright in the CCSI Toolset was updated to include the year 2025. The code and notes within it were revised to correct minor typographical errors and clarify meanings of variables. The configuration of the FOQUS documentation via Read the Docs was updated to explicitly set the path.

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DOE OSTI2021

Reliability and Maintainability Changing the Culture

The Reliability and Maintainability team strives to ensure the reliability, availability, and maintainability of plant assets throughout their life cycle. This objective is accomplished by providing world-class maintenance engineering support and maintenance processes. University of Tennessee’s Reliability and Maintainability Center (UT RMC) Partnership – Provided subject matter expert (SME) analysis of current state of both sites integrated work control (IWC) and maintenance execution processes.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Connected and Learning Based Optimal Freight Management for Efficiency

The management of the future heterogenous fleet is a complex decision-making problem. The heterogenous fleet is emerging as decarbonization technologies are deployed by fleets toward lowering the freight operation emissions in Medium and Heavy-duty vehicles. Traditionally, in fleets characterized by a homogeneous Diesel Internal Combustion Engine (ICE) powertrain, the process of fleet planning and operational optimization unfolds sequentially without the necessity to account for powertrain and vehicle-specific characteristics during dispatch decisions. Fleets with trucks less than 5 years old tend to maintain stable vehicle efficiency with minimal operational reliability risks for fleet managers. However, the landscape changes with the incorporation of emerging powertrain technologies, which lack extensive operational data and service experiences. This includes technologies like hybrid, Electric, Fuel Cell, or alternative fuel ICE. Operational decisions for fleets featuring heterogeneous powertrain technologies and facing limited access to alternative fueling and charging stations become intricate, requiring careful consideration and optimization at each dispatch. The difference in efficiency characteristics of emerging technologies, their range limitations, and the restricted availability of charging/alternative fueling infrastructure, coupled with sensitivity to driving conditions (e.g., EV range reduction in low temperatures) and their impact on component aging (such as batteries), become pivotal factors influencing the reliable and efficient freight transportation. To make the path toward low emission freight transportation efficient and reliable, an AI-assisted fleet management software is developed in this project to help fleet managers in optimizing both adoption of emerging powertrain decarbonization, connected and automated technologies and also operating the fleet after such technologies are deployed as schematically. Freight transportation requirements are different depending on the cargos to be shipped, customer requirements and regions of operations. This further highlights the need for software and digital solutions to tailor deployment and operation of emerging powertrain, connectivity, and automation technologies toward the specific fleet operation requirements. The fleet management optimizer was also integrated with a model of the fleet to simulate the operation of the fleet over 1 year of the baseline fleet operation (250,000+ shipments) indicating the significance of day-to-day variations on emissions and energy consumption of a freight transportation fleet. The results demonstrate ≥20% improvement in freight efficiency in terms of WTW CO2 per ton-mile of cargo shipments while all fleet operation constraints are enforced, and the cost (CapEx and OpEx) is minimized.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Overview and Status of the Long-Baseline Neutrino Facility Far Detectors Cryogenics System

The Sanford Underground Research Facility (SURF) will host the Far Detectors of the Deep Underground Neutrino Experiment (DUNE), an international multi-kiloton Long-Baseline neutrino experiment that will be installed about a mile underground in Lead, SD. Detectors will be located inside four cryostats filled with almost 70,000 metric tons of ultrapure liquid argon, with a level of impurities lower than 100 parts per trillion of oxygen equivalent. The cryogenics infrastructure supporting this experiment is provided by the Long- Baseline Neutrino Facility (LBNF). This contribution presents modes of operation, layout and main features of the LBNF Far Detectors cryogenics system, which is composed of the following subsystems: argon receiving facilities, nitrogen system, argon distribution system, argon purification and regeneration systems, argon circulation system, argon condensers system, internal cryogenics, miscellaneous items, and process controls. An international engin eering tea m is designing these systems and will manufacture, install, test, commission, and qualify them. This contribution describes the main features, performance, functional requirements, and modes of operation of the LBNF Far Detectors cryogenics system. It also presents the status of the design, along with present and future needs to support the DUNE experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Radiation Effects on Network on Chips (NoC) Laboratory Directed Research and Development (LDRD) project

This project was motivated by State-of-the-Art (SOTA) technology that incorporates Network on Chips (NOC) for efficient data communication across the various computer kernels. For example, on the AMD Versal Field Programmable Gate Arrays (FPGA), an NoC has been incorporated for fast data communication from the programmable logic and other computer kernels (processing system, adaptable intelligence engines, etc.). The radiation effects on the legacy technology of this FPGA, such as the programmable logic, are well understood, and established methods exist to measure cross-sections when new families/generations are released; however, newly incorporated technologies, such as the NoC, are not fully understood and could introduce new failure points into the mission space.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Processed data from the Building Management System for the System Engineering Building.

The dataset spans November 2018 to May 2020 and includes time-series measurements corresponding to supply and return temperatures of air and water, air, hot water and cold water flow rates, energy and power consumption, set-points etc. as a single CSV file. In addition to the measurements, a metadata .json file, and a .ttl file to visualize the data as per BRICK schema are also included.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗